All Episodes
Displaying 31 - 60 of 323 in total
Practical workflow orchestration
Workflow orchestration has always been a pain for data scientists, but this is exacerbated in these AI hype days by agentic workflows executing arbitrary (not pre-defi...
Towards high-quality (maybe synthetic) datasets
As Argilla puts it: “Data quality is what makes or breaks AI.” However, what exactly does this mean and how can AI team probably collaborate with domain experts toward...
Understanding what's possible, doable & scalable
We are constantly hearing about disillusionment as it relates to AI. Some of that is probably valid, but Mike Lewis, an AI architect from Cincinnati, has proven that h...
GraphRAG (beyond the hype)
Seems like we are hearing a lot about GraphRAG these days, but there are lots of questions: what is it, is it hype, what is practical? One of our all time favorite pod...
Pausing to think about scikit-learn & OpenAI o1
Recently the company stewarding the open source library scikit-learn announced their seed funding. Also, OpenAI released “o1” with new behavior in which it pauses to “...
Cybersecurity in the GenAI age
Dinis Cruz drops by to chat about cybersecurity for generative AI and large language models. In addition to discussing The Cyber Boardroom, Dinis also delves into cybe...
AI is more than GenAI
GenAI is often what people think of when someone mentions AI. However, AI is much more. In this episode, Daniel breaks down a history of developments in data science, ...
Metrics Driven Development
How do you systematically measure, optimize, and improve the performance of LLM applications (like those powered by RAG or tool use)? Ragas is an open source effort th...
Threat modeling LLM apps
If you have questions at the intersection of Cybersecurity and AI, you need to know Donato at WithSecure! Donato has been threat modeling AI applications and seriously...
Only as good as the data
You might have heard that “AI is only as good as the data.” What does that mean and what data are we talking about? Chris and Daniel dig into that topic in the episode...
Gaudi processors & Intel's AI portfolio
There is an increasing desire for and effort towards GPU alternatives for AI workloads and an ability to run GenAI models on CPUs. Ben and Greg from Intel join us in t...
Broccoli AI at its best 🥦
We discussed “🥦 Broccoli AI” a couple weeks ago, which is the kind of AI that is actually good/healthy for a real world business. Bengsoon Chuah, a data scientist work...
Hyperventilating over the Gartner AI Hype Cycle
This week Daniel & Chris hang with repeat guest and good friend Demetrios Brinkmann of the MLOps Community. Together they review, debate, and poke fun at the 2024 Gart...
The first real-time voice assistant
In the midst of the demos & discussion about OpenAI’s GPT-4o voice assistant, Kyutai swooped in to release the first real-time AI voice assistant model and a pretty sl...
Vectoring in on Pinecone
Daniel & Chris explore the advantages of vector databases with Roie Schwaber-Cohen of Pinecone. Roie starts with a very lucid explanation of why you need a vector data...
Stanford's AI Index Report 2024
We’ve had representatives from Stanford’s Institute for Human-Centered Artificial Intelligence (HAI) on the show in the past, but we were super excited to talk through...
Apple Intelligence & Advanced RAG
Daniel & Chris engage in an impromptu discussion of the state of AI in the enterprise. Then they dive into the recent Apple Intelligence announcement to explore its im...
The perplexities of information retrieval
Daniel & Chris sit down with Denis Yarats, Co-founder & CTO at Perplexity, to discuss Perplexity’s sophisticated AI-driven answer engine. Denis outlines some of the de...
Using edge models to find sensitive data
We’ve all heard about breaches of privacy and leaks of private health information (PHI). For healthcare providers and those storing this data, knowing where all the se...
Rise of the AI PC & local LLMs
We’ve seen a rise in interest recently and a number of major announcements related to local LLMs and AI PCs. NVIDIA, Apple, and Intel are getting into this along with ...
AI in the U.S. Congress
At the age of 72, U.S. Representative Don Beyer of Virginia enrolled at GMU to pursue a Master’s degree in C.S. with a concentration in Machine Learning.Rep. Beyer is ...
First impressions of GPT-4o
Daniel & Chris share their first impressions of OpenAI’s newest LLM: GPT-4o and Daniel tries to bring the model into the conversation with humorously mixed results. To...
Full-stack approach for effective AI agents
There’s a lot of hype about AI agents right now, but developing robust agents isn’t yet a reality in general. Imbue is leading the way towards more robust agents by ta...
Autonomous fighter jets?!
Yep, you heard that right. Autonomous fighter jets are in the news. Chris and Daniel discuss a modified F-16 known as the X-62A VISTA and autonomous vehicles/ systems ...
Private, open source chat UIs
We recently gathered some Practical AI listeners for a live webinar with Danny from LibreChat to discuss the future of private, open source chat UIs. During the discus...
Mamba & Jamba
First there was Mamba… now there is Jamba from AI21. This is a model that combines the best non-transformer goodness of Mamba with good ‘ol attention layers. This resu...
Udio & the age of multi-modal AI
2024 promises to be the year of multi-modal AI, and we are already seeing some amazing things. In this “fully connected” episode, Chris and Daniel explore the new Udio...
RAG continues to rise
Daniel & Chris delight in conversation with “the funniest guy in AI”, Demetrios Brinkmann. Together they explore the results of the MLOps Community’s latest survey. Th...
Should kids still learn to code?
In this fully connected episode, Daniel & Chris discuss NVIDIA GTC keynote comments from CEO Jensen Huang about teaching kids to code. Then they dive into the notion o...
AI vs software devs
Daniel and Chris are out this week, so we’re bringing you conversations all about AI’s complicated relationship to software developers from other Changelog pods: JS Pa...